• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.5
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• pp.381-388
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• 2014

Our aim was to simulate ocean waves in a small-size wave flume and observe the motion of a cylindrical floating body placed in an offshore environment. To precisely visualize the oscillation of the body, a set of light-emitting diode illuminators and high-speed charge-coupled device camera were installed in the flume. Spectral analysis was performed of the movement of the floating body. The wave generator and absorbers worked well to simulate stable regular waves. As the period of the oncoming waves changed, the movement of the floating body substantially differed when tethered to a tension-leg mooring cable. In particular, when connected to the tension-leg mooring cable, the natural frequency of the floating body suddenly appeared at 0.391 Hz as the wave period was increased.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.147-154
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• 2006

The final purpose of this study is to explore morphological change of Shenyang in the period of the rising Chung Dynasty. For that purpose we have tried to build the historical GIS DB of site and analysis of the structure and shape pattern of the city by using the functions of GIS. From the view of spatial structure and cultural context, main characteristics, which is derived from the analysis of ancient map of Shenyang, can be summarized into five things as follows ; transformation of open spatial structure into closed structure, combination of horizontal spatial structure with vertical structure, transformation of practical spatial structure into symbolic structure, transformation of natural spatial structure into institutional form of ancient Chinese capital city, conservation of traditional Manchurian culture.

• The Journal of Engineering Geology
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• v.15 no.1
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• pp.1-8
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• 2005

As a trial to find an efficient technique for determining hydraulic conductivity, a test application of electrical conductivity measurement technique was made using a signal conditioning data acquisition system in borehole. The experiment was made in two test boreholes BM-2 and BM-3 which are located in the Experiment forests of Kangwon National University in Bongmyongri, Chunchon. We obtained series of electric conductivity variation curves after the beginning and completion of saline water injection using these two bore-holes as the pumping well and the observing well alternatively, The analysis of time series electrical conductivity data suggests kinds of valuable information about aquifer properties by holes and depths, and we could confirm the potential of this method as an efficient tool for in situ aquifer test.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.10
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• pp.166-174
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• 1998

Neural networks, having highly nonlinear dynamics by virtue of the distributed nonlinearities and the learing ability, have the potential for the adaptive prediction of nonstationary signals. This paper describes the nonlinear prediction of these signals in two ways; using a nonlinear module and the cascade combination of nonlinear and linear modules. Fully-connected recurrent neural networks (RNNs) and a conventional tapped-delay-line (TDL) filter are used as the nonlinear and linear modules respectively. The dynamic behavior of the proposed predictors is demonstrated for chaotic time series adn speech signals. For the relative comparison of prediction performance, the proposed predictors are compared with a conventional ARMA linear prediction model. Experimental results show that the neural networks based adaptive predictor ourperforms the traditional linear scheme significantly. We also find that the cascade combination predictor is well suitable for the prediction of the time series which contain large variations of signal amplitude.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.447-454
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• 2010

This paper presents multiple fuzzy prediction systems based on an Interval type-2 TSK fuzzy Logic System so that the uncertainty and the hidden characteristics of nonlinear data can be reflected more effectively to improve prediction quality. In proposed method, multiple fuzzy systems are adopted to handle the nonlinear characteristics of data, and each of multiple system is constructed by using interval type-2 TSK fuzzy logic because it can deal with the uncertainty and the characteristics of data better than type-1 TSK fuzzy logic and other methods. For input of each system, the first-order difference transformation method are used because the difference data generated from it can provide more stable statistical information to each system than the original data. Finally, computer simulations are performed to show the effectiveness of the proposed method for two typical time series examples.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.29-34
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• 2017

Recently, studying chaotic dynamic have been concerned by many researchers in areas of physics, chemistry, mathematics, engineering and social science. Especially, model of addiction, happiness, family and love become major research subjects in the social science. Among these models, love is one of the four emotions that human being have. There are many definitions for love, however, each definitions of love does not coincide with each other. Recently, one of the most important efforts for research is love and it is represented by derivative equation. Then they try to find nonlinear or chaotic behavior from this derivative equation. This paper propose Gaussian fuzzy membership function in order to make external force that are close to action and awareness of human based on love model of Romeo and Juliet with external force. This paper also confirms the existence of nonlinear characteristics through time series and phase portrait.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.284-284
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• 2023

도시 침수의 발생과 규모는 도시 유역이 가지는 짧은 도달 시간으로 인하여 주로 시단위 이하의 짧은 지속시간의 강우의 극한 및 변동성에 따라 결정된다. 미래 기간에 대하여 도시 수문 시스템의 적정성을 평가하기 위해서는 기후변화에 따른 시단위 이하 강우의 특성을 살펴보아야한다. 그러나 기후변화 영향 평가 도구로 활용되는 기후 모형들은 대부분 일단위의 결과물을 제공하여 시단위 이하의 미세 규모 강우의 특성을 나타낼 수 없다. 이에 따라 본 연구에서는 기후 모형 모의 결과와 포아송 클러스터 강우 모형을 이용하여 미래 시단위 이하 강우 시계열을 모의하는 방법을 제안한다. 첫째로, 포아송 클러스터 기반 강우 생성 알고리즘과 폭풍우 재배열 알고리즘을 결합한 최신 모형을 선정하였다. 해당 모형은 광범위한 시간 규모에서 관측된 강우량의 주요 통계와 극값을 재현할 수 있는 모형이다. 그 다음 강우 모형에 적합시킬 관측 강우량 통계(평균, 분산, 공분산, 왜도, 우기 비율)를 계산하였다. 둘째, 강우 통계 간의 선형 관계를 도출하였다. 여기서는 클러스터에 있는 모든 관측소의 통계를 사용하여 회귀의 신뢰도를 높였다. 셋째, 강우 평균 조정을 위한 Change Factor는 제어(2000~2019년) 및 미래(2041~2070년) 기간의 기후 모형 자료를 사용하여 계산하였다. 넷째, 조정된 15분 강우 평균은 관측 평균에 Change Factor을 곱하여 계산하고 조정된 강우 평균과 통계 간의 관계를 사용하여 미래 강우 통계 세트를 추정하였다. 여러 통계 세트를 생성한 후 마지막으로 미래 통계에 강우 모형을 적합시켜 최종적으로 미래 시단위 이하 강우 시계열을 모의하였다. 이 방법은 CMIP6에 참여하는 기후 모델의 기후 예측 데이터를 사용하여 용산(415) 및 동래(940) AWS 관측소에 적용되었다. 두 관측소의 미래 강우 모의 결과, 시단위 이하 시간 규모에서 극값이 증가하는 추세를 보였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.115-115
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• 2023

최근 기후변화의 영향으로 국내에서 강우량과 유출량의 변동성이 커짐에 따라 효율적으로 수자원을 관리하는 데 어려움을 겪고 있다. 따라서 수자원 관리 측면에서 강우관측소를 대상으로 군집 분석과 경향성 분석을 통해 사전에 강우 시계열 자료의 추세와 특징을 파악하면 용수 공급과 가뭄 및 홍수피해 저감 등에 효과적으로 대처할 수 있다. 본 연구에서는 2000년부터 2019년까지낙동강 유역의 64개 강우관측소를 대상으로 동질성 검정과 수정 Mann-Kendall (MK) 검정을 적용하여 강우 시계열 자료의 월별, 계절별, 연도별 경향성 분석을 수행하였다. 또한, 경향성이 나타나는 관측소별 세부지표(연평균 강우량, 표고 등)를 기준으로 K-means 군집 분석을 수행하여 군집별 강우 특성을 파악하고자 하였다. 분석을 수행한 결과 경향성 분석에선 3월, 4월, 11월, 12월, 봄 및 가을에는 강우량이 증가 추세를 보였고 1월, 5~9월, 여름과 연도별로는 감소 추세가 나타났다. 또한 군집 분석에서는 Silhouette analysis를 기반으로 최적의 군집 개수를 3개로 설정했을 때 군집별 강우 세부지표의 통계값이 관측소별 표고에 비례하는 특징이 나타났다. 연구를 통해 도출된 군집별 강우 특성과 관측소별 경향성 분석결과를 연계하면 강우량의 변동성을 고려한 효율적인 수자원 관리 방안을 마련하는 데 활용할 수 있을 것으로 판단된다.

• Economic and Environmental Geology
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• v.39 no.3 s.178
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• pp.269-284
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• 2006

Aquifer responses to the river stage fluctuations were analyzed between the groundwater level and the river stage in an alluvial aquifer. The auto-correlation and cross-correlation as a time series analysis were applied. Study site is a floodplain in the Mangyeong river. Groundwater levels in each depth representing the silt and sand(SS), gravel and sand(GS), and weathered zone(WZ) layer were monitored. The groundwater levels were more sensitive to the river stage fluctuations than rainfall. Since the river stages are influenced by the gate operations downstream and tide, show periodic patterns, and the correlation coefficients with rainfall is low. Cross-correlation function between groundwater level in each depth do not show any delay time, then response time is very short to each depth. Cross-correlation analysis were performed to estimate the response time of groundwater levels to river stage fluctuations. Groundwater levels respond to the river stage within 30 minutes to 1 hour in wells near the stream. Short time lag between groundwater level and river stage indicates the quick response. A different response time imply the hydraulic inhomogeneity of the site, and a probable high permeability zone between river and aquifer can be inferred. Mangyeong-river in study site is a gaining stream normally, and river stage rising by gate operation or floods makes river water flow into groundwater. The auto-correlation and cross-correlation functions as a time series analysis can be a good tool to interpret the aquifer responses to stream stage fluctuation

• Journal of Technology Innovation
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• v.27 no.4
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• pp.21-48
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• 2019

In the basic research field, quantitative expansion is carried out with active support from the government, but there is no research and policy data suggesting systematic investment plans or data-based financial requirements yet. Therefore, this study predicted future financial requirements of basic research support programs by using time series prediction model. In order to consider various factors including the characteristics of the basic research field, we selected the ARIMAX model which can reflect the effect of multi valuable factors rather than the ARIMA model which predicts the value of single factor over time. We compared the predictions of ARIMAX and ARIMA models for model suitability and found that the ARIMAX model improves the prediction error rate. Based on the ARIMAX model, we predicted the fiscal spending of basic research support programs for five years from 2017 to 2021. This study has significance in that it considers the financial requirements of the basic research support programs as a pilot research conducted by applying a time series model, which is a statistical approach, and multi-variate rather than single-variate. In addition, considering the policy trends that emphasize the importance of basic research investment such as 'the expansion of basic research budget twice', which is the current government's national policy task, it can be used as reference data in establishing basic research investment strategy.